Minimum quantity lubrication advantages when applied to insert flank face in milling

Werda, Sana; Duchosal, Arnaud; Quilliec, Guénhaël Le; Morandeau, Antoine; Leroy, René

doi:10.1007/s00170-017-0317-y

Cited by 12 publications

(20 citation statements)

References 24 publications

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“…Shi et al (2016) investigated tool wear behaviors and their effect on machinability in dry high-speed milling of magnesium alloy at high cutting speeds. Werda et al (2017) compared tool life and surface roughness in the milling of X100CrMoV5 mold steel under different lubrication conditions: dry machining and minimum quantity lubrication (MQL). Even though many authors (Diniz and Filho 1999;Caldeirani Filho and Diniz 2002;De Souza et al 2003, 2005De Escalona and Maropoulos 2010;Prasad et al 2011;Houchuan et al 2015;Liu et al 2016;Shi et al 2016;Werda et al 2017) have presented the results of surface roughness studies that take into account tool wear, no solutions to the problem of how to establish a comprehensive correlation of surface roughness, tool wear, and processing time have been advanced from the perspective of managing these settings in automated production.…”

Section: Introductionmentioning

confidence: 99%

“…Much of the research devoted to the study of surface roughness in face milling (Diniz and Filho 1999;Caldeirani Filho and Diniz 2002;De Souza et al 2003, 2005De Escalona and Maropoulos 2010;Prasad et al 2011;Houchuan et al 2015;Liu et al 2016;Shi et al 2016;Werda et al 2017) takes tool wear into account. Diniz and Filho (1999) studied the influence of the relative positions of tool and workpiece on tool life, tool wear, and surface finish in the face milling process, taking tool wear into account.…”

Section: Introductionmentioning

confidence: 99%

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Artificial intelligence for automatic prediction of required surface roughness by monitoring wear on face mill teeth

2017

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Nowadays, face milling is one of the most widely used machining processes for the generation of flat surfaces. Following international standards, the quality of a machined surface is measured in terms of surface roughness, Ra, a parameter that will decrease with increased tool wear. So, cutting inserts of the milling tool have to be changed before a given surface quality threshold is exceeded. The use of artificial intelligence methods is suggested in this paper for real-time prediction of surface roughness deviations, depending on the main drive power, and taking tool wear, V B into account. This method ensures comprehensive use of the potential of modern CNC machines that are able to monitor the main drive power, N , in real-time. It can likewise estimate the three parameters -maximum tool wear, machining time, and cutting power-that are required to generate a given surface roughness, thereby making the most efficient use of the cutting tool. A series of artificial intelligence methods are tested: random forest (RF), standard Multilayer perceptrons (MLP), Regression Trees, and radial-based functions. Random forest was shown to have the highest model accuracy, followed by regression trees, displaying higher accuracy than the standard MLP and the radial-basis function. Moreover, RF techniques are easily tuned and generate visual information for direct use by the process engineer, such as the linear relationships between process parameters and roughness, and thresholds for avoiding rapid tool wear. All of this information can be directly extracted from the tree structure or by drawing 3D charts plotting two process inputs and the predicted roughness depending on workshop requirements. Keywords

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Artificial intelligence for automatic prediction of required surface roughness by monitoring wear on face mill teeth

2017

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“…Finally, in a turning study of SCM440H, the surface roughness of the workpiece was improved by the oil mist supplied to the flank face over a large cutting speed range of 30-300 m min À1 compared to rake face lubrication [20]. Recently, in previous experiments [21], the influence of MQL lubrication position in milling X100CrMoV5 steel has been investigated. Results showed that the efficiency of MQL process was ensured when applied to flank face.…”

Section: Introductionmentioning

confidence: 99%

“…Results showed that the efficiency of MQL process was ensured when applied to flank face. The lubricant penetrated the tool/workpiece interface which led to a lower surface roughness of about 40% and better tool life of 10% compared to MQL applied on rake face [21]. From the above studies, flank face lubrication is generally a better choice than rake face lubrication in turning and in milling.…”

Section: Introductionmentioning

confidence: 99%

“…In order to understand the wear mechanisms and such different behaviours when MQL was applied on rake face and flank face, tribological tests need to be considered. Hence, a tribological study was represented in this article to determine frictional behaviour regarding milling strategy to investigate the results in the previous study [21]. Two types of tribometers can be used: closed tribometers and opened tribometers.…”

Section: Introductionmentioning

confidence: 99%

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Effect of minimum quantity lubrication strategies on tribological study of simulated machining operation

Werda

Duchosal

Quilliec

et al. 2019

Mechanics & Industry

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The main aim of this paper was to reproduce the frictional behaviour that occurred in milling with a pin-on-cylinder system. Three different tribological tests were conducted reproducing friction phenomenon that happened in three machining conditions: (i) dry rubbing, representing the dry machining condition, (ii) MQL applied to front face rubbing which was similar to milling with MQL applied on the insert rake face and (iii) MQL applied to rear end rubbing which was similar to milling with MQL applied on flank face. Tribological tests were carried out with coated tungsten carbide pins rubbing on X100CrMoV5 steel cylinder. Apparent coefficient of friction, adhesion area and heat flux transmitted to the pin were analysed. It has been shown that MQL rear end rubbing provided a lower adhesion area and lower apparent coefficient of friction than with MQL front face rubbing. Furthermore, MQL rear end rubbing resulted in a greater cooling ability. These findings helped to explain why better results were obtained with MQL flank face lubrication in milling compared to MQL rake face lubrication.

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Multi-response Optimization in Face Milling of EN-31 Steel Using Hybrid CRITIC and DFA Technique

Sharma¹,

Singh²,

Singh³

et al. 2023

Lecture Notes in Mechanical Engineering

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Minimum quantity lubrication advantages when applied to insert flank face in milling

Cited by 12 publications

References 24 publications

Artificial intelligence for automatic prediction of required surface roughness by monitoring wear on face mill teeth

Artificial intelligence for automatic prediction of required surface roughness by monitoring wear on face mill teeth

Effect of minimum quantity lubrication strategies on tribological study of simulated machining operation

Multi-response Optimization in Face Milling of EN-31 Steel Using Hybrid CRITIC and DFA Technique

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